Document Type
Conference Paper
Publication Date
2-2015
Publication Source
Proceedings of SPIE 9405, Image Processing: Machine Vision Applications VIII
Abstract
Hyperspectral imaging (HSI) sensors provide plenty of spectral information to uniquely identify materials by their reflectance spectra, and this information has been effectively used for object detection and identification applications. Joint transform correlation (JTC) based object detection techniques in HSI have been proposed in the literatures, such as spectral fringe-adjusted joint transform correlation (SFJTC) and with its several improvements.
However, to our knowledge, the SFJTC based techniques were designed to detect only similar patterns in hyperspectral data cube and not for dissimilar patterns. Thus, in this paper, a new deterministic object detection approach using SFJTC is proposed to perform multiple dissimilar target detection in hyperspectral imagery. In this technique, input spectral signatures from a given hyperspectral image data cube are correlated with the multiple reference signatures using the classassociative technique.
To achieve better correlation output, the concept of SFJTC and the modified Fourier-plane image subtraction technique are incorporated in the multiple target detection processes. The output of this technique provides sharp and high correlation peaks for a match and negligible or no correlation peaks for a mismatch. Test results using real-life hyperspectral data cube show that the proposed algorithm can successfully detect multiple dissimilar patterns with high discrimination.
Inclusive pages
940502-1 to 940502-7
ISBN/ISSN
0277-786X
Document Version
Published Version
Copyright
Copyright © 2015, Society of Photo-optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited.
Publisher
Society of Photo-optical Instrumentation Engineers
Place of Publication
San Francisco, CA
Volume
9405
eCommons Citation
Sidike, Paheding; Asari, Vijayan K.; and Alam, Mohammad S., "Multiple Object Detection in Hyperspectral Imagery Using Spectral Fringe-Adjusted Joint Transform Correlator" (2015). Electrical and Computer Engineering Faculty Publications. 379.
https://ecommons.udayton.edu/ece_fac_pub/379
Comments
This document is provided for download in compliance with the publisher's policy on self-archiving. Permission documentation is on file.
DOI: http://dx.doi.org/10.1117/12.2076798